Clichés of scientific writing

Novel writers use an average of 100 clichés for every 100 000 words. Or about one every four pages. That’s what Ben Blatt found by comparing a range of novels against a list of 4000 clichés. How does scientific writing compare?

In one sense, scientific writing avoid clichés. A scientist isn’t going to write that their new results put the nail in the coffin of the outgoing theory, that they were careful to dot their i’s and cross their t’s so as to follow the methods of Jones et al. by the book, that Brown et al.’s finding is a diamond in the rough, or that two possible interpretations are six of one and half a dozen of the other.

In another sense, scientific writing is full of clichés. Our writing often feels like a fill in the blanks: the results of this study show X, these findings are in good agreement with Y, or Z is poorly understood and needs further study. Need more examples? Checkout the Manchester Academic Phrasebank, a collection of phrases from the academic literature that are “content neutral and generic in nature.”

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Remove cognitive overhead from your scientific papers

“There is this scientific convention of: ‘You put the images on one side, then you put the text to decipher it on the other side.’” That’s Jonathan Corum, science graphics editor for the New York Times, politely critiquing one of the ways in which a typical scientific paper creates unnecessary work for the reader, or “cognitive overhead.”

Decipher is the key word above (and a word I’ll use again below). If deciphering is necessary, it will precede understanding, but that doesn’t mean it is necessary. “No one intends to build a product with large cognitive overhead, but it happens if there isn’t forethought and recognition for it.”

eye_movement_opt
A poorly designed figure. The reader’s eyes to have to dart back and forth between the panels, the colour bars, the labels, and the caption. This unnecessary work inhibits a deeper understanding of the data.

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My favourite word is appreciably: overused words in scientific writing

Every writer leaves a hidden fingerprint in their texts whether they know it or not. It’s hidden in the relative usage of words: some words appear more than average and other words less. Imagine there’s a rumour that a well established author has written a new book under a pen name, but they’re are pretending that this is not the case. One piece of evidence that the authors are one in the same is to count the number mundane words like and, but or -ly adverbs used within the new book and then compare the numbers to the author’s past works. Authors use surprisingly similar numbers of each word over the length of a book. Don’t believe me? Then check out Ben Blatt’s book Nabokov’s Favorite Word is Mauve.

The title of this post is a nod to Blatt’s book. In this, he statistically analyses word frequency in a range of texts from literature to fan fiction to New York Times bestsellers. He uses numbers to teach us about writing. Early on, he shows how a reduction in usage of -ly adverbs correlates with a book’s appeal. This is but one of many predictors of a text’s success based only on word frequency. In the same vein, I’m going to scrutinise my own scientific writing to find room for improvement. Navel-gazing? Yes. Will you learn something if you read on? Also yes.

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Don’t start paragraphs with Figure n shows …

This article is going to describe … would be a terrible opening for this article. It’s six words that convey nothing. You already know this is an article, and you already know that it’s going to describe something. We don’t see this, fortunately, because the importance of a strong and compelling opening sentence is well recognised. At the paragraph level, however, it’s easy to forget the importance of the first sentence. In scientific cases, a symptom of poor or lazy writing is opening a paragraph with Figure n shows.

When it comes to visualising your data, the most important question to ask yourself is what’s your point. Wording a paragraph by starting with Figure n shows will not convey the point. It tells me what you did, but not why I should care. Using this phrase would be like putting the Methods section of a scientific paper before the Introduction.

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